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The Evolution of SOCs with Gen AI

Edward Wu
May 29, 2024

Managing security within a Security Operations Center (SOC) requires swift and precise alert assessment to maintain effective cybersecurity measures. On average, SOC teams are inundated with 4,484 alerts daily, dedicating hundreds of FTE hours to manually triaging them. This substantial volume strains resources and increases the potential for errors in threat prioritization and response. 

While some existing solutions are designed to alleviate the burden on staff and enhance threat detection accuracy, many of these measures often fall short of fully addressing the challenges. In this article, we explore the challenges of managing a SOC and dive deep into how AI can reduce the load for a more accurate assessment of threats.

SOC Challenges

SOCs play a crucial role in protecting organizational digital assets, yet they face significant challenges in SOCs play a crucial role in protecting organizational digital assets, yet they face significant challenges in managing and responding to the growing volume of security alerts. Cyber threats continuously evolve in complexity and frequency, making it more difficult for SOCs to sift through a vast influx of alerts and promptly identify and address critical issues. This overwhelming flow can lead to alert fatigue among analysts, potentially causing delayed or overlooked responses to actual threats.

Staffing Challenges

Staffing SOCs with skilled individuals is challenging. Organizations continue to grow, adopting new technologies such as cloud and AI to improve efficiency and agility. However, this growth comes with rapidly increasing attack surfaces and significantly larger volumes of security data flowing into SOCs. 

All of this additional data has increased the demand for skilled security professionals. However, there simply aren’t enough qualified candidates, with 3.5 million unfilled cybersecurity positions by 2025. The supply is nowhere near fulfilling overall needs, making filling these positions costly, so merely increasing staff numbers is not viable. 

Despite the staffing deficiencies, organizations continue to generate thousands of alerts from their dozens of tools daily, overwhelming existing SOC teams. This overload of alerts leads to alert fatigue for security professionals, increasing pressure on staff and causing burnout. Churn from this burnout is at historic levels, with staff leaving organizations where they feel stressed and starting at others, leading to increased stress levels among those left behind, impacting their well-being and organizational operational efficiency. Organizations must be mindful of these challenges and take steps to support their security teams. Overwhelmed employees may miss crucial alerts buried under false positives or fail to connect the dots on potential risks due to inadequate data correlation, leading to significant security oversights.

Complex Toolsets

Adding to this challenge is the complexity of toolsets within SOCs. This complexity can significantly contribute to operational inefficiencies and increased response times, ultimately hindering a SOC’s effectiveness in mitigating cyber risks. 

As cyber defense systems become more intricate, diverse tools can create a fragmented security landscape where data and alerts are isolated across various platforms. This fragmentation compels analysts to navigate multiple systems to gather and correlate information, making identifying and responding to threats more time-consuming and increasing the likelihood of errors. 

Additionally, the steep learning curve associated with mastering these complex tools can exacerbate the skills gap within cybersecurity teams, further straining their resources and reducing their ability to respond swiftly and accurately to potential threats.

Understanding Current Solutions

The current market is well aware of the challenges inherent in managing SOCs and has developed various solutions to address these issues, though each solution only partially mitigates the problems. Technologies such as SOAR and chatbots have been introduced to alleviate some of the burdens teams face. These tools provide some relief but only partially solve the underlying problems. They help reduce the workload but do not entirely eliminate the operational inefficiencies or the complexity of navigating between different security tools.


One solution to help streamline and automate workflows across various security tools is Security Orchestration, Automation, and Response (SOAR). These platforms focus on orchestrating processes and automating repetitive tasks to enhance operational efficiency. They rely on predefined rules and playbooks for automated responses to common security scenarios, ideally allowing SOCs to react swiftly and effectively without manual intervention for every alert. 

However, these platforms are not ready to run out of the box. They require considerable setup and customization, as creating effective playbooks and defining appropriate rules is very complex and time-intensive. Each playbook can only cover 1 scenario, which forces the customer to write hundreds of playbooks to achieve any level of significant automation.


Chatbots are another potential answer to this problem. They are primarily designed for interactive Q&A and serve as tools for assistance or guidance in a conversational format, responding to user inputs. While they do create an in-depth knowledge base powered by AI for analysts to draw on, the additional resources come at a steep cost. Chatbots create a constant cycle of staff prompting and awaiting answers, adding additional steps to micromanage rather than simplifying the work. This is much akin to a painter being hired to paint a wall but requiring the customer to prompt them before every paint stroke is made.

Leveraging Recent Advancements in Gen AI

AI technology in cybersecurity has made remarkable strides in recent years, transforming from basic automation tools into sophisticated systems capable of predictive and proactive security measures. Legacy AI typically excelled at narrow tasks and relied heavily on large labeled datasets and manual feature engineering. In contrast, Gen AI can handle complex, multi-step decision-making processes and automate intricate tasks involving natural language, such as customer service and content creation. This adaptability and learning efficiency enables it to automate more complex tasks in dynamic environments that involve fuzzy decision making which legacy AI simply can’t handle.

By automating routine and complex tasks alike, Gen AI frees up human work to focus on strategic issues that require human insight, significantly enhancing productivity and decision-making capabilities in various applications.

Supporting SOC Analysts

Gen AI significantly alleviates the burden on cybersecurity analysts by automating high-volume, repetitive tasks that previously consumed a significant portion of their workday. This shift allows human SOC analysts to focus their expertise on more complex, strategic areas of cybersecurity that demand human ingenuity and critical thinking. By doing so, AI SOC analysts, powered by Gen AI, speed up the threat identification process - helping analysts quickly separate false positives from real threats—and enhance human analysts’ capacity to engage in deeper, more meaningful analyses. As a collaborative intelligence partner, AI integrates advanced computational power with human expertise, improving the SOC’s responsiveness and decision-making accuracy, thereby enhancing the overall security posture.

Enhancing SOC Efficiency

In a different vein, Gen AI dramatically boosts the overall efficiency of threat management systems within SOCs by optimizing the processing and evaluation of security alerts. This capacity for rapid data processing enables SOCs to shift human resources from reactive to proactive projects, eliminating the opportunities for potential threats before they manifest. The scalability of AI is crucial in managing the ever-increasing data volume without the need to proportionally increase the number of staff. Over time, AI’s adaptive learning capabilities allow it to become more adept at recognizing and responding to new threats in each environment, continuously enhancing the operational efficiency of SOCs. This dynamic improvement supports SOCs in developing more sophisticated, forward-thinking defense strategies.

Comparing Solutions

The advantages of Gen AI autonomous SOC analysts over the current solutions discussed become far more apparent as we compare current technology.

Eliminating Rigid Playbooks

AI SOC analysts represent a new category in cybersecurity technology, specializing in autonomous, Gen AI-driven analysis and decision-making for tier-1 alert investigations. This innovative approach enhances the quality of alert analysis and significantly reduces the workload for human analysts. Unlike traditional security solutions that rely on predefined rules and playbooks to automate and orchestrate responses, AI SOC analysts utilize the latest advancements in Generative AI to autonomously handle analysis and decision-making, minimizing the need for constant human intervention.

While effective in some generic environments, traditional automation solutions often require extensive work to adapt to more diverse or dynamic settings. Their effectiveness heavily depends on the meticulous configuration and maintenance of automation rules and playbooks. In contrast, AI SOC analysts do not require any pre-programming or playbooks and are designed for ease of use with minimal setup. They offer organizations complete tier-1 alert investigation automation out-of-the-box. These Gen AI analysts can adapt more fluidly to each deployed environment without requiring user involvement and resource allocation to update and maintain playbooks.

By leveraging advanced AI capabilities, AI SOC analysts bring a significant shift in how cybersecurity threats are managed, offering a more adaptive and proactive approach to security that traditional automated systems struggle to match.

How AI SOC Analysts Streamline Alert Investigations

AI SOC analysts are designed to handle end-to-end alert investigations autonomously without human intervention. The AI SOC analysts, powered by Gen AI, excel at processing a large volume of routine, tier-1 security alerts autonomously, thereby significantly reducing the workload on human analysts. Conventional security solutions, including those enhanced by legacy AI, generally require more interaction and iterative communication with users to achieve a comprehensive analysis. In contrast, AI SOC analysts are capable of sophisticated threat analysis and management within SOCs, making them highly effective for organizations aiming to streamline their security operations and improve their overall security posture.

Revolutionize Your SOC Operations with Advanced AI SOC Analysts

AI SOC analysts are the next undeniable evolution in security operations centers (SOCs), designed to transform how alerts and incidents are managed. These AI-driven analysts enable security teams to focus their expertise on high-level strategic tasks by automating the analysis and response to complex security alerts. This shift enhances the efficiency of SOC operations, strengthens the overall security posture, and optimizes the allocation of human resources.

Experience the future of Gen AI-driven security operations. Schedule a demo today to discover how AI SOC analysts can streamline and elevate your SOC. See the transformative power of this advanced technology in action, marking a significant leap forward in cybersecurity management.